How to Design using Data

When designing products, teams always need some kind of starting point they can use to base their efforts on. This can be an existing design or previous version of a product that needs improvement as well as design guidelines and heuristics. However another way to start off your process is to use data and the resulting insights to guide and inform your design choices.
This approach is called data-driven design and its main goal is to help the end users of the resulting products understand the product itself as well as how it works. Making sure you use the insights you gathered to ensure your product fits users preferences, needs, expectations and goals will most likely result in a seamless and pleasant user experience.

Why should you design data-driven?

The process of developing and designing products and their UX is always influenced by multiple stakeholders. Different stakeholders tend to have different goals and expectations how the finished product is supposed to look. Your first impulse might be to meet the expectations of investors and higher-ups. However your main goal should always be to please the end-user of the product.
Assuming your end-user has a pleasant and efficient experience using your product, they are more likely to convert or even recommend the product to friends and colleagues. In the long run this should result in increased sales and please other stakeholders as well.

Using data also helps teams to check whether they are moving in the right direction and actually working towards reaching their goal. It can also help you discover future opportunities for your product, pain points the users might encounter as well as new patterns and trends. Get to know your users on a deeper level by observing their behavior and uncovering the reasons for their actions. Ultimately your research will provide you with objective results you can use to improve your design.

How to get started with data-driven design

Even if you don’t think so: you most likely already possess data about your users and customers in some form. Of course data for better design can specifically be gathered with user tests and surveys, but you can also use the data stored in user databases as well as website analytics. You can use this trail of data left behind by every user and website visitor to get to know you target group and create a more tailored and compelling design.
To get started, use your existing data and website analytics to analyze users’ behavior and use resulting insights to improve your existing personas. As a next step you can use these personas to run user tests with participants that match your target group closely. The data gathered during these user tests can in turn be used to flesh out your data sets further, improve your design and iterate your product.
Having gathered your existing data you can also try to compile and organize it in order to find gaps where further information is needed. Once these gaps have been identified you can systematically start closing them by conducting further research. Try to combine qualitative and quantitative data. Adding the results of user tests and screen recordings to your data may seem like a daunting task but will give you deeper, enriched insights into the way your users think.

Why is data-driven Design important and what are the benefits?

The quantitative data you gathered can be understood using descriptive statistics and appropriate visualization. Qualitative data can be evaluated using experience and common-sense combined with past observations. When trying to build usable products your users will enjoy, you have to employ both. While design is often based on instinct, data can help understand why things are a certain way and help you justify decisions towards stakeholders.
One problem that arises when design is based on instinct is the well known fact that designer ≠ user. Even the most experienced designers can’t always predict what the user wants or needs. This problem becomes more grave as the differences between designers and users increase. Contrary to the beliefs of certain designers, most of the time users actually do know what they want. Especially if there are already products on the market that are in any way similar to what you plan to develop, users will have an idea of what they want of your product or expect it to do. Luckily this gap between designer and user can be bridged with user-testing.


While it might sound counter-intuitive to connect data and analysis with creativity, user data and insights can help designers find new directions and move past best practices. Insights can be used to combat assumptions and help designers gain the courage to modify or even completely ignore best practices. While guidelines and design-rules are based on facts and experience and certainly useful under certain circumstances, you shouldn’t follow them blindly or you risk ending up with a product that looks like everybody else’s.
Putting the user first and designing a smooth, pleasant experience will result in a more effective, easier to use product. Being informed about the end users’ needs and wants can help solve problems more efficiently. Data can be employed to back up design decisions and justify why the design team chose to deviate from common best practices to better adapt to users’ needs.

Remove the guesswork

Pairing the work of UX professionals with data analysis and user research will help teams eliminate most of the guesswork in the design process. As stated above: when in doubt, most of the time teams rely on widely accepted principles, heuristics and established design guidelines. Still they are pretty much just guessing what their specific target group actually wants. Understanding users’ behavior, their context of use and behavioral patterns will give the design process a clear direction.
Usually some kind of data already exists before the design work even begins. This data can be used to gain first insights and modify a product to better meet users’ expectations even before the first “real” user-test has been run. Working data-driven can give clear guidelines that make the design process more user-centric and efficient.

You need a tool that helps you analyze your research results? We’re working on the solution for you: Consider.ly makes it possible for you and your team to create searchable recharche findings and helps you spot patterns assisted by AI. For any questions, please send us an E-Mail.